• The KIPS Transactions:PartA
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• v.13A no.4 s.101
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• pp.275-288
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• 2006

Rapid design space exploration is crucial to customizing embedded system design for exploiting the application behavior. As the time-to-market becomes a key concern of the design, the approach based on an application specific instruction-set processor (ASIP) is considered more seriously as one alternative design methodology. In this approach, the instruction set architecture (ISA) for a target processor is frequently modified to best fit the application with regard to code size and speed. Two goals of this paper is to introduce our new retargetable compiler and how it has been used in ASIP-based design space exploration for a popular digital signal processing (DSP) application. Newly developed retargetable compiler provides not only the functionality of previous retargetable compilers but also visualizes the features of the application program and profiles it so that it can help architecture designers and application programmers to insert new application specific instructions into target architecture for performance increase. Given an initial RISC-style ISA for the target processor, we characterized the application code and incrementally updated the ISA with more application specific instructions to give the compiler a better chance to optimize assembly code for the application. We get 32% performance increase and 20% program size reduction using 6 audio codec specific instructions from retargetable compiler. Our experimental results manifest a glimpse of evidence that a higgly retargetable compiler is essential to rapidly prototype a new ASIP for a specific application.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.371-380
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• 2004

E-commerce is in wide use with the rapid advance of internet technology. The main component of an e-commerce application is a Web-based database application. Currently, it takes a lot of time in developing Web applications since developers should write codes manually or semi-automatically for user interface forms and query processing of an application. Therefore, the productivity increase of Web-based database applications has been demanded. In this paper, we introduce a software tool, which we call the WebSiteGen2, that automatically generates the forms that we used as user interfaces and the EJB/JSP components that process the query made through the forms for an application that needs a new database or uses an existing database. The WebSiteGen2 thus increases the productivity, reusability, expandibility, and portability of an application by automatically generating a 3-tier application based on component technology. Moreover, one user interface form that are generated by the WebSiteGen2 provides information on an interested entity as well as information on all the directly or indirectly related entities with the interested one. In this paper, we explain the functionality and implementation of the WebSiteGen2 and then show the merits by comparing the WebSiteGen2 to the other commercial Web application generators.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.97-97
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• 2013

Recently, Cu2ZnSn(S,Se)4 (CZTSS), which is one of the In- and Ga- free absorber materials, has been attracted considerable attention as a new candidate for use as an absorber material in thin film solar cells. The CZTSS-based absorber material has outstanding characteristics such as band gap energy of 1.0 eV to 1.5 eV, high absorption coefficient on the order of 104 cm-1, and high theoretical conversion efficiency of 32.2% in thin film solar cells. Despite these promising characteristics, research into CZTSS based thin film solar cells is still incomprehensive and related reports are quite few compared to those for CIGS thin film solar cells, which show high efficiency of over 20%. I will briefly overview the recent technological development of CZTSS thin film solar cells and then introduce our research results mainly related to sputter based process. CZTSS thin film solar cells are prepared by sulfurization of stacked both metallic and sulfide precursors. Sulfurization process was performed in both furnace annealing system and rapid thermal processing system using S powder as well as 5% diluted H2S gas source at various annealing temperatures ranging from $520^{\circ}C$ to $580^{\circ}C$. Structural, optical, microstructural, and electrical properties of absorber layers were characterized using XRD, SEM, TEM, UV-Vis spectroscopy, Hall-measurement, TRPL, etc. The effects of processing parameters, such as composition ratio, sulfurization pressure, and sulfurization temperature on the properties of CZTSS absorber layers will be discussed in detail. CZTSS thin film solar cell fabricated using metallic precursors shows maximum cell efficiency of 6.9% with Jsc of 25.2 mA/cm2, Voc of 469 mV, and fill factor of 59.1% and CZTS thin film solar cell using sulfide precursors shows that of 4.5% with Jsc of 19.8 mA/cm2, Voc of 492 mV, and fill factor of 46.2%. In addition, other research activities in our lab related to the formation of CZTS absorber layers using solution based processes such as electro-deposition, chemical solution deposition, nano-particle formation will be introduced briefly.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.171-183
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• 2018

Despite the rapid expansion of satellite images supply, the application of imagery is often restricted due to unautomated image processing. This paper presents the automated process for the selection of training areas which are essential to conducting supervised image classification. The training areas were selected based on the prior and cover information. After the selection, the training data were used to classify land cover in an urban area with the latest image and the classification accuracy was valuated. The automatic selection of training area was processed with following steps, 1) to redraw inner areas of prior land cover polygon with negative buffer (-15m) 2) to select the polygons with proper size of area ($2,000{\sim}200,000m^2$) 3) to calculate the mean and standard deviation of reflectance and NDVI of the polygons 4) to select the polygons having characteristic mean value of each land cover type with minimum standard deviation. The supervised image classification was conducted using the automatically selected training data with Sentinel-2 images in 2017. The accuracy of land cover classification was 86.9% ($\hat{K}=0.81$). The result shows that the process of automatic selection is effective in image processing and able to contribute to solving the bottleneck in the application of imagery.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.12
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• pp.295-300
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• 2018

The rapid development of IT, many conventional passive jobs have been automated. This automation increases the leisure time of many people and various services are being developed for them. In addition, with the advent of smart devices that are compact and portable, it is possible to use various internet services without any time and place discretion. Various studies based on virtualization are under way to efficiently store and process large data generated by many devices and services. Desktop Storage Virtualization (DSV), which integrates and provides users with on-premise-based distributed desktop resources during these studies, uses virtualization to consolidate unused resources within distributed, legacy desktops. This DSV is very important for providing high reliability to users. In addition, research on hierarchical structure and resource integration for efficient data distribution storage processing in a distributed desktop-based resource integration environment is underway. However, there is a lack of research on efficient operation in case of server failure in on-premise resource integration environment. In this paper, we propose Non-disruptive Server Management (NSM) which can actively cope with the failure of desktop server in distributed desktop storage environment based on on-premise. NSM is easy to add and remove desktops in a desktop-based integrated environment. In addition, an alternative server is actively performed in response to a failure occurrence.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.457-464
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• 2021

The advent of the big data era has enabled the rapid development of deep learning that learns rules by itself from data. In particular, the performance of CNN algorithms has reached the level of self-adjusting the source data itself. However, the existing image processing method only deals with the image data itself, and does not sufficiently consider the heterogeneous environment in which the image is generated. Images generated in a heterogeneous environment may have the same information, but their features may be expressed differently depending on the photographing environment. This means that not only the different environmental information of each image but also the same information are represented by different features, which may degrade the performance of the image analysis model. Therefore, in this paper, we propose a method to improve the performance of the image color constancy model based on Adversarial Learning that uses image data generated in a heterogeneous environment simultaneously. Specifically, the proposed methodology operates with the interaction of the 'Domain Discriminator' that predicts the environment in which the image was taken and the 'Illumination Estimator' that predicts the lighting value. As a result of conducting an experiment on 7,022 images taken in heterogeneous environments to evaluate the performance of the proposed methodology, the proposed methodology showed superior performance in terms of Angular Error compared to the existing methods.

• Resources Recycling
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• v.31 no.6
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• pp.81-91
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• 2022

The use of lithium-ion batteries increases significantly with the rapid spread of electronic devices and electric vehicle and thereby an increase in the amount of waste batteries is expected in the near future. Therefore, studies are continuously being conducted to recover various resources of cathode active material (Ni, Co, Mn, Li) from waste battery. In order to recover the cathode active material, black mass is generally recovered from waste battery. The general process of recovering black mass is a waste battery collection - discharge - dismantling - crushing - classification process. This study focus on the crushing/classification process among the processes. Specifically, the particle size distribution of various samples at each crushing/classification step were evaluated, and the particle shape of each particle fraction was analyzed with a microscope and SEM (Scanning Electron Microscopy)-EDS(Energy Dispersive Spectrometer). As a result, among the black mass particle, fine particle less than 74 ㎛ was the mixture of cathode and anode active material which are properly liberated from the current metals. However, coarse particle larger than 100 ㎛ was present in a form in which the current metal and active material were combined. In addition, this study developed a PBM(Population Balance Model) system that can simulate two-species mixture sample with two different crushing properties. Using developed model, the breakage parameters of two species was derived and predictive performance of breakage distribution was verified.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.315-324
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• 2023

In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.127-135
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• 2023

With the development of information and communication technology, the amount of information produced and shared in the battlefield and stored and managed in the system dramatically increased. This means that the amount of information which cansupport situational awareness and decision making of the commanders has increased, but on the other hand, it is also a factor that hinders rapid decision making by increasing the information overload on the commanders. To overcome this limitation, this study proposes a method to automatically search, select, and summarize documents that can help the commanders to understand the battlefield situation reports that he or she received. First, named entities are discovered from the battlefield situation report using a named entity recognition method. Second, the documents related to each named entity are discovered. Third, a language model and collaborative filtering are used to select the documents. At this time, the language model is used to calculate the similarity between the received report and the discovered documents, and collaborative filtering is used to reflect the commander's document reading history. Finally, sentences containing each named entity are selected from the documents and sorted. The experiment was carried out using academic papers since their characteristics are similar to military documents, and the validity of the proposed method was verified.